Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Parallel Processing

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Activating Phase-Transition Toughening in van der Waals Semiconductor GaTe.

Nano letters·2026

Same author

Differential Image Sensor With Decoupled Static and Dynamic Outputs.

Advanced materials (Deerfield Beach, Fla.)·2026

Same author

Gradient-distributed metal-halide dynamic memristors for adaptive and robust voiceprint recognition.

Nature communications·2026

Same author

Resolving intrinsic dislocation structure in perovskite crystals using pulsed electron beam with atomic resolution.

Nature communications·2026

Same author

Curvature-programmed nitrate electroreduction via single-atom protrusions on quantum dots.

Science advances·2026

Same author

Nanofluid-Assisted Synthesis of High-Entropy Alloy Nanoparticles.

Journal of the American Chemical Society·2026

Search research articles

Related Experiment Video

Updated: Sep 14, 2025

Bidirectional Electrical and Optoelectronic Interfaces in Healthy and Ischemic Ex Vivo Rat Hearts

Bidirectional Electrical and Optoelectronic Interfaces in Healthy and Ischemic Ex Vivo Rat Hearts

Published on: July 18, 2025

2D Materials for Emerging Neuromorphic Vision: From Devices to In-Sensor Computing.

Pengshan Xie¹, Dengji Li¹, Weijun Wang¹

¹Department of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, China.

Small (Weinheim an Der Bergstrasse, Germany)

|July 24, 2025

Summary

This summary is machine-generated.

Two-dimensional (2D) materials offer a solution for energy-efficient edge visual processing by enabling in-sensor computing. This approach overcomes the limitations of traditional architectures for intelligent vision systems.

Keywords:

2D semiconductor artificial synapse neuromorphic computing optoelectronic device

More Related Videos

Fabrication of Flexible Image Sensor Based on Lateral NIPIN Phototransistors

Fabrication of Flexible Image Sensor Based on Lateral NIPIN Phototransistors

Published on: June 23, 2018

Optical Control of Living Cells Electrical Activity by Conjugated Polymers

Optical Control of Living Cells Electrical Activity by Conjugated Polymers

Published on: January 28, 2016

Related Experiment Videos

Last Updated: Sep 14, 2025

Bidirectional Electrical and Optoelectronic Interfaces in Healthy and Ischemic Ex Vivo Rat Hearts

Bidirectional Electrical and Optoelectronic Interfaces in Healthy and Ischemic Ex Vivo Rat Hearts

Published on: July 18, 2025

Fabrication of Flexible Image Sensor Based on Lateral NIPIN Phototransistors

Fabrication of Flexible Image Sensor Based on Lateral NIPIN Phototransistors

Published on: June 23, 2018

Optical Control of Living Cells Electrical Activity by Conjugated Polymers

Optical Control of Living Cells Electrical Activity by Conjugated Polymers

Published on: January 28, 2016

Area of Science:

Materials Science
Neuromorphic Engineering
Computer Architecture

Background:

The von Neumann architecture struggles with energy efficiency and real-time processing for edge visual applications due to data transfer bottlenecks.
Two-dimensional (2D) materials offer atomic-scale thickness, tunable optoelectronics, and integration flexibility, making them suitable for in-sensor computing.
Current material systems include ferroelectric 2D materials, topological insulators, and twistronic systems for enhanced perception, computation, and storage.

Purpose of the Study:

To provide a comprehensive overview of advancements in 2D material systems for in-sensor computing.
To explore the operational mechanisms and visual perceptual functions of these 2D materials.
To examine the integration of deep learning architectures with 2D material systems for intelligent vision.

Main Methods:

Review of recent literature on 2D material systems for neuromorphic vision.
Analysis of operational mechanisms, including polarization sensing and spectral selection.
Investigation of device integration strategies and deep learning algorithm compatibility.

Main Results:

2D materials enable efficient perception, computation, and storage within a single device, overcoming von Neumann bottlenecks.
Specific 2D material systems demonstrate capabilities for polarization sensing and spectral selection.
Integration strategies are being developed to merge deep learning with 2D material-based visual neural synaptic devices.

Conclusions:

2D materials are a promising solution for energy-efficient, real-time visual processing in edge applications.
Merging materials innovation with neuromorphic engineering can lead to intelligent vision systems.
In-sensor computing using 2D materials overcomes the limitations of traditional computer architectures.